Tuesday, July 2, 2013

New paper finds in retrospect, we predicted global warming would slow for only 5 years

A paper recently published in Nature Climate Change claims to "retrospectively predict" the "pause" in global warming due to Trenberth's "missing heat" sinking undetected to the bottom of the ocean. Close examination of the paper, however, reveals that the model used by the authors only predicted a slowdown for up to 5 years, not the complete lack of warming for the past 16+ years. Buried in the paper is the admission that "The reasons for the warming pause to be sustained late in the decade have not however been clearly identified from our [modelling] experiments." Furthermore the authors admit, "The deep-ocean heat uptake has been argued to be largely overestimated by most climate models, which does not seem to be the case for [the author's model], although the scarce observations do not constrain to firm conclusions about the deep ocean." In other words, the one model that allegedly "retrospectively predicted" lack of warming said it would last only up to 5 years, there has been no warming for 16+ years, we don't know why, and we don't have deep ocean observations to back up our claims.

Despite a sustained production of anthropogenic greenhouse gases, the Earth’s mean near-surface temperature paused its rise during the 2000–2010 period1. To explain such a pause, an increase in ocean heat uptake below the superficial ocean layer2, 3 has been proposed to overcompensate for the Earth’s heat storage. Contributions have also been suggested from the deep prolonged solar minimum4, the stratospheric water vapour5, the stratospheric6 and tropospheric aerosols7. However, a robust attribution of this warming slowdown has not been achievable up to now. Here we show successful retrospective predictions of this warming slowdown up to 5 years ahead, the analysis of which allows us to attribute the onset of this slowdown to an increase in ocean heat uptake. Sensitivity experiments accounting only for the external radiative forcings do not reproduce the slowdown. The top-of-atmosphere net energy input remained in the [0.5–1]Wm−2 interval during the past decade, which is successfully captured by our predictions. Most of this excess energy was absorbed in the top 700m of the ocean at the onset of the warming pause, 65% of it in the tropical Pacific and Atlantic oceans. Our results hence point at the key role of the ocean heat uptake in the recent warming slowdown. The ability to predict retrospectively this slowdown not only strengthens our confidence in the robustness of our climate models, but also enhances the socio-economic relevance of operational decadal climate predictions.

At a glance

The recent global warming slowdown despite the sustained top-of-atmosphere (TOA) excess energy input associated with the greenhouse gases triggered a debate on the fate of the missing heat2, 3, 4, 5, 6, 7, 8. A potential absorption of this heat by the atmosphere, the land or the sea ice has been ruled out using observational data sets8. Dissecting the internally generated variability in a climate model, this warming slowdown has been argued2 to come partly from an increased radiation to space, associated with the El Niño/Southern Oscillation variability, and partly from increased deep-ocean warming, associated with the Atlantic meridional overturning circulation. An internal origin of this warming slowdown was suggested in another climate model3, mostly related to a deep-ocean heat uptake associated with both the subtropical Pacific circulation and Atlantic meridional overturning circulation variability.

Near-term climate prediction9, 10, 11 offers an optimal framework to test the hypotheses suggested in the literature to explain the observed twenty-first-century warming slowdown. At the edge between seasonal forecasting and climate-change projections, near-term climate predictions exploit the predictability of the climate system arising both from initializing the internal natural variability and from the changes in radiative external forcings12, whereas climate projections benefit only from the latter. Successful retrospective predictions thus stand as an opportunity to attribute this warming slowdown to the interannual internal variability or the radiative external forcings, whereas observation analysis alone allows for detection and drawing of hypotheses but not for any attribution. The ability of the present generation of climate forecast systems to capture the pause in sea surface temperature (SST) rise from 2000 onward is not only crucial for adaptation but also a new challenge for climate modellers1.

Such a challenge is taken up with the EC-Earth forecast system13, 14 in the Init experiment in which all of the model state variables are initialized from estimates of the observed climate state, namely from the ORAS4 reanalysis15, 16 for the ocean component, from the ERA40 reanalysis17 for the atmosphere and land surface before 1989 and the ERAinterim18 one afterwards, and from two different sources of sea-ice initial conditions (see Methods for further details). In those retrospective predictions initialized every November from 1960 to 2011, the ensemble-mean SST averaged over the first 3 forecast years (Fig. 1a) is very close to the observed 3-year running mean SST in all of the predictions from 2000 onward (one large dot per ensemble-mean prediction). The root mean square error (RMSE) computed from the ensemble-mean forecasts initialized between 2001 and 2005 is 0.027K and spans the range [0.026–0.059]K for the individual ensemble members. On average over the forecast years 3–5, the warming slowdown is slightly less well captured with the RMSE reaching 0.052 [0.044–0.087]K (Fig. 1b). It is still however, much better captured than in the NoInit sensitivity experiment (in blue), which does not include any information about the previous history of the observed variability but only information about the radiative external forcing prescribed as in Init. The equivalent RMSE in NoInit is 0.100 [0.058–0.120]K (Fig. 1c). Initializing the EC-Earth forecast system from estimates of the observed climate state substantially improves its performance in predicting the global SST of the past decade. The computation of the 3-year SST tendency along each forecast provides further insight into the ability of the EC-Earth forecast system to capture the mechanism leading to such a warming slowdown. The 3-year mean SST changes (Fig. 1d) are computed as the difference between the 3-year mean SST after and before the year indicated in the x axis. The 3-year mean SST changes are better captured in Init than NoInit in the core of the warming slowdown, which means that the ability of EC-Earth to forecast the warming slowdown beyond 3 years does not come only from persistence of the initial conditions (also illustrated in Supplementary Fig. S1) but largely from its ability to capture the processes leading to the warming slowdown. Initializing the forecast system with the contemporaneous dynamical and thermodynamical climate system state seems crucial to capture the negative SST tendency, although this negative tendency is underestimated.

Figure 1: Ability to capture the warming slowdown.

a–c, Global SST anomalies averaged between 60°S and 65°N and across forecast years 1–3 (a,c) and forecast years 3–5 (b). d, 3-year mean SST change along the forecasts. One large dot is shown for the ensemble mean of each forecast and small dots are shown for their members in Init (red). The equivalents in NoInit and in the observations are shown in blue and black respectively, joined by lines as they come from a continuous time series.

In spite of the warming slowdown, the observed CERES TOA net radiative flux remained positive (downward) during the early twenty-first century as shown in Fig. 2a in black. Both Init and NoInit reproduce this positive net TOA radiative flux and stand within the observational uncertainty estimated as 0.38 and 0.5Wm−2 in different studies19, 20. Supplementary Fig. S2 shows that most of the TOA excess energy is absorbed by the ocean–sea ice system and Supplementary Fig. S3illustrates that the contribution of the sea-ice system to this energy absorption amounts to about 1%, thus leaving the ocean as the main contributor. The negligible contributions from the atmosphere, land and sea ice are consistent with previous findings8. The 3-year accumulated global ocean heat uptake in the ORAS4 ocean reanalysis, computed as the difference between the 3-year mean total-column ocean heat content (OHC) after and before the year indicated in the xaxis (Fig. 2b), is consistent with the TOA excess energy within the observational uncertainty. The ORAS4 ocean heat uptake shows a peak reaching about 0.55×1023J at the beginning of the warming slowdown, which exceeds slightly the TOA excess energy at the same date, therefore accounting for the atmosphere and land surface cooling. The ORAS4 total OHC anomalies show consistently a sharp increase from 2000 (Fig. 3). The peak in ORAS4 ocean heat uptake around 2002 stands as the largest ocean heat uptake ever recorded over the whole observational period (Fig. 3d). The Init total OHC anomalies follow closely the ORAS4 ones until the third forecast year (Fig. 3a) and are still in reasonable agreement with ORAS4 until forecast year 5 (Fig. 3b) whereas NoInit OHC (Fig. 3c) barely exhibits any oscillation around the long-term warming trend. The 3-year accumulated ocean heat uptake along the different forecasts in Init (in red, Figs 2b and 3d) illustrates that the peak is captured by EC-Earth and also stands as the largest peak in ocean heat uptake ever simulated by EC-Earth. Although underestimated, the ocean heat uptake is about 50%larger in Init than NoInit during the peak in the early warming slowdown (Fig. 2b). A proper initialization seems crucial to simulate the penetration of the heat into the ocean with the correct timing, and hence its impact on the global warming slowdown in the past decade.

Figure 2: Earth’s heat budget.

a–g, Init, NoInit and the observational data are shown in red, blue and black, respectively. In a–c, one large symbol shows the ensemble mean, and small symbols show the individual members. Observations from CERES (a) and ref. 21 (0–700m) (c) are shown with squares, with their observational uncertainty19, 21shaded in grey. ORAS4 (ocean reanalysis) is shown with dots (b–c), triangles and diamonds (d–g). The contribution from the total column (b) and from the total 0–724m layer (c), are shown with dots for ORAS4, Init and NoInit. In d–g, the contribution from the ocean mixed layer and from the 0–724m layer excluding the mixed layer are shown respectively with triangles and diamonds.

a–c, Total global OHC anomalies averaged across forecast years 1–3 (a,c) and forecast years 3–5 (b).d, 3-year accumulated heat uptake along the forecasts. One large dot is shown for the ensemble mean of each forecast and small dots are shown for their members in Init (red). The equivalents in NoInit and in the ORAS4 reanalysis are shown in blue and black respectively, joined by lines as they come from a continuous time series.

The peak in total ocean heat uptake (Fig. 2b) is mostly explained by the upper (0–724m) ocean (Fig. 2c) where the corresponding peak is captured by Init, but similarly underestimated as compared with ORAS4. Such a peak also appears in the best estimate of 0–700m OHC available so far21 shown with squares. The ocean mixed-layer heat content (Fig. 2d, triangles) exhibits a similar stabilization or slight decrease as the SST whereas the layer below (diamonds) is responsible for the peak. The decomposition per basin (Fig. 2e–g) highlights the tropical Pacific, the tropical Atlantic and the North Atlantic absorption below the mixed layer (diamonds) as the main contributors to this enhanced ocean heat uptake. Those basins explain 42%, 25% and 16% of the upper ocean heat uptake at the time of its maximum, respectively. Supplementary Fig. S4 illustrates the negligible contribution of other regions. The ocean heat uptake below the mixed layer exceeds slightly the TOA excess energy, therefore accounting for the observed cooling of the land, near-surface atmosphere and ocean superficial layer. Supplementary Fig. S5 provides further insight into the spatial distribution of the ocean heat uptake estimated from several observational data sets. Although occurring too early, the peak in tropical Pacific OHC absorption below the mixed layer is captured by Init with correct amplitude (Fig. 2e and Supplementary Fig. S6), but not by NoInit (Supplementary Fig. S7). The Init tropical Atlantic OHC tendency follows the ORAS4 one closely (Fig. 2f). However, the North Atlantic peak is completely missed by Init (Fig. 2g), hence its underestimation of the total-column ocean heat uptake (Fig. 2b) and SST tendency (Fig. 1d). The benefits from the initialization in capturing the spatial distribution of the ocean heat uptake during the onset of the warming pause are further illustrated in Supplementary Fig. S8.

Whereas some previous modelling studies2, 3 suggested an increase in deep-ocean heat uptake as the main cause for the recent hiatus, such a hypothesis does not explain the onset of the warming slowdown either in the ORAS4 reanalysis, or in the EC-Earth retrospective predictions. The deep-ocean heat uptake has been argued4 to be largely overestimated by most climate models, which does not seem to be the case for EC-Earth, although the scarce observations do not constrain to firm conclusions about the deep ocean. Suggested contributions from the deep prolonged solar minimum4, the stratospheric water vapour5, the stratospheric4, 6 and tropospheric aerosols7 would be associated with a decrease in the net TOA energy imbalance to produce a warming slowdown such as the one recently observed. Here, we have shown that the contribution from variations in the external radiative forcing to the onset of the hiatus is negligible and that the initialization of EC-Earth from estimates of the observed climate state is essential to capture this warming slowdown (Fig. 1). At the onset of the warming pause, the TOA excess energy input is mainly absorbed in the upper 700m ocean below the ocean mixed layer (Fig. 2), which confirms a previous hypothesis19 drawn from observational analyses. The reasons for the warming pause to be sustained late in the decade have not however been clearly identified from our [modelling] experiments. This climate prediction exercise has thus allowed for an attribution of the onset [only] of the hiatus to an enhanced ocean heat uptake.

Although initialization is necessary to predict natural variability, improved predictions of the slowdown do not necessarily mean that natural variability is entirely responsible, because initialization can also correct errors in the model's response to external factors. Nevertheless, a successful model simulation can be further analysed to understand the physical processes at play. Guemas et al. did this by tracking energy changes in their model. They found that the input of energy at the top of the atmosphere remained constant during the slowdown, showing that factors that would have altered this — such as changes in aerosols, solar radiation or stratospheric water vapour — did not play an important role in their model. Instead, the slowdown was initiated by the largest uptake of heat by the upper ocean in the historical record, which warmed the ocean below the surface without affecting surface waters.

This offers a plausible explanation for the onset of the warming slowdown, although further work is needed to understand relationships between upper ocean and surface temperatures, and the processes by which heat was buried below the surface. However, the lack of warming beyond 2004 is still not understood7. According to observations8, energy continues to be accumulated through the top of the atmosphere, but has not been taken up by the upper ocean. This leaves the deep ocean as the most likely destination, but this cannot be confirmed because the observational network is too sparse. There is therefore an urgent need for observations of the deep ocean, as well as continued monitoring of energy fluxes at the top of the atmosphere.